Target tracking or object tracking is a family of algorithms which are used in a range of applications. One branch of this family is the point-based tracking in which objects are represented by points, contrary to the two other typical branches: kernel-based tracking and silhouette-based tracking.
In point-based tracking, shown in FIG. 1 to which reference is now made, the input to the point-based tracking algorithm 14 is often the raw data 10 from one or more sensors after adequate preprocessing 12, and is habitually termed snapshots. This is a stream of D-dimensional arrays, indexed by the acquisition time t. A vector of indices, p∈D, of an array element is a position, and a series of positions {p (t)}t=1T, indexed by the acquisition time t is termed a trajectory and is the output of the point-based tracking algorithm 14.
The point-based tracking algorithm 14 is composed of a detection mechanism 16 to detect the objects in every snapshot, and an association mechanism 18 to associate the objects to trajectories. The detection 16 is generally performed using thresholding, while employing deterministic or probabilistic tools. The association 18 is typically divided into three methods: Kalman filter (KF), particle filter (PF) and multiple hypothesis tracking (MHT), which generally track across snapshots by evolving the objects' state (e.g., object position and motion).
For example, in radar applications, the raw data received from the antennas normally undergoes manipulations, such as frequency conversion to baseband, matched filtering, Fourier transform and modulus (a.k.a. absolute value) to create a Range-Doppler map (RDM), which is a 2-dimensional real-positive-valued array with indices Rmin≤r≤Rmax and Vmin≤v≤Vmax indicating the range and the Doppler velocity of each cell. The detection stage 16 is often based on thresholding, either a static or a dynamic one, where cells with a modulus exceeding a certain threshold over the neighbourhood is detected as an object. For example, assuming such an object in a cell which is described by a vector of indices p(t)=[r(t) v(t)]T ∈2, where r(t) and v(t) are, respectively, the range and the Doppler velocity at time t, the trajectory {[r(t) v(t)]T}t=1T is the output of the point-based tracking algorithm.